Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy
Palak Handa, Amirreza Mahbod, Florian Schwarzhans, Ramona Woitek, Nidhi Goel, Manas Dhir, Deepti Chhabra, Shreshtha Jha, Pallavi Sharma, Vijay Thakur, Simarpreet Singh Chawla, Deepak Gunjan, Jagadeesh Kakarla, Balasubramanian Raman
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- github.com/sri-karthik-avala/capsule-challenge-2024OfficialIn paperpytorch★ 2
- github.com/reubenjrouse/VCap_CapsuleVision2024Officialpytorch★ 1
- github.com/misahub2023/capsule-vision-2024-challengeOfficialIn papertf★ 0
- github.com/i-am-tobi/Capsule_Vision_Challenge_2024Officialpytorch★ 0
- github.com/GirinChutia/Misahub-Capsule-Vision-2024-Solution-eAIOfficialpytorch★ 0
- github.com/ajay-pratap-singh-518/Capsule-Vision-2024-challengeOfficialpytorch★ 0
- github.com/flux661/Capsule-Vision-2024-Solution-Team_Layer_PlayersOfficialtf★ 0
Abstract
We present the Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy. It was virtually organized by the Research Center for Medical Image Analysis and Artificial Intelligence (MIAAI), Department of Medicine, Danube Private University, Krems, Austria in collaboration with the 9th International Conference on Computer Vision & Image Processing (CVIP 2024) being organized by the Indian Institute of Information Technology, Design and Manufacturing (IIITDM) Kancheepuram, Chennai, India. This document provides an overview of the challenge, including the registration process, rules, submission format, description of the datasets used, qualified team rankings, all team descriptions, and the benchmarking results reported by the organizers.